Department of Statistics, The Wharton School, University
of Pennsylvania

Monday, March 5, 2007
4:10 p.m.
223 Weber

ABSTRACT

Malaria is an infectious disease caused by a parasite that is an
important public health problem in many countries. A major symptom
of malaria is fever. An important epidemiological quantity for
measuring the burden of malaria is the proportion of fevers that are
attributable to malaria, called the malaria attributable fraction
(MAF). A difficulty in estimating the MAF is that it is difficult to
diagnose a fever as being due to malaria parasites compared to other
illnesses such as influenza, pneumonia, viral hepatitis or typhoid
fever. Microscopic examination of blood for malaria parasites helps
to diagnose a fever as being due to malaria, but children living in
areas of high malaria endemicity often tolerate malaria parasites
without developing any signs of disease; consequently, a fever may
not be attributable to malaria even if the child has malaria
parasites in his or her blood. We consider estimation of the MAF
based on data on fever incidence and parasite density in the blood.
We present a potential outcomes framework for defining the MAF, and
analyze previously proposed estimators in this framework. We show
that the classical estimator depends on an assumption that parasite
densities among children are effectively randomly assigned, and
present evidence that this assumption does not hold. We develop a
sensitivity analysis that assesses the sensitivity of inferences to
departures from a random assignment of parasite densities assumption.